Virtual screening and invitro evaluation of cyclooxygenase inhibitors from Tinospora cordifolia using the machine learning tool.

Tinospora cordifolia has a variety of compounds, and some of these compounds may have anti-inflammatory and antioxidant properties. In the present study, we identified the compounds in the leaf extract of T. cordifolia through Gas Chromatography-Mass Spectrometry (GC-MS) analysis and found the various metabolites. The compounds are screened virtually using a machine learning model, followed by molecular docking and simulation study to identify top-hit compounds as cyclooxygenase (COX) inhibitors. The molecular docking revealed that the compound 7,9-Di-tert-butyl-1-oxaspiro (4,5) deca-6,9-diene-2,8-dione (CID:545303) exhibited the lowest binding energies of -7.1 and -6.8 kcal/mol against COX 1 and COX 2 respectively. The interactions are favored by hydrogen bonding and hydrophobic interaction inside the binding pocket. The 100 ns MD simulation study for these compounds was performed to know the stability and found the RMSD around 2 Å and around 1.0 Å with minimal fluctuations indicating a stable complex throughout the simulation of 100 ns. Based on these findings, we proposed 7,9-Di-tertbutyl- 1-oxaspiro (4,5) deca-6,9-diene-2,8-dione could be used as a dual inhibitor of COX enzymes and a drug-like molecule for treating inflammation after evaluation of their biological properties. The methanolic extract of T. cordifolia was subjected to in vitro DPPH, ABTS, nitric oxide, anti-microbial, COX, and LOX inhibition activity. The results exhibited possible positive effects against the above activities.Communicated by Ramaswamy H. Sarma.

An in silico study on pulmonary fibrosis inhibitors from Tinospora cordifolia and Curcuma longa targeting TGF-ß RI.

Pulmonary fibrosis is characterized by damage to the epithelial cells and alveolar-capillary basement membrane. The increased expression levels of transforming growth factor ß (TGF-ß) and TGF-ß-receptor-1 induced differentiation of lung fibroblasts to myofibroblasts, an alarming sign and considered the hallmark event development of pulmonary fibrosis. In the current study, the stability of phytochemicals of Curcuma longa and Tinospora cordifolia as inhibitors of transforming growth factor ß RI (TGF-ß RI) were evaluated using molecular docking and molecular dynamics studies. A total of 108 Curcuma longa and 16 Tinospora cordifolia constituents were screened against TGF-ß RI as the target. Further, their ADMET properties were evaluated using the pkCSM online server. The compounds tembetarine, magnoflorine from T. cordiolia, and 2-(Hydroxymethyl) anthraquinone and quercetin in C. longa showed significant binding affinities bonding interactions with the target, TGF-ß RI, and the study was compared with the known inhibitors from the literature. The MD simulations study also supported that the selected compounds show a close affinity with the binding site and maintained stable behavior throughout the simulation time. The pharmacophore feature analysis of the selected compounds and inhibitors were analyzed using the pharmagist web server, and the common features like H-bond donor and aromatic ring were mapped.Communicated by Ramaswamy H. Sarma.

Molecular modeling study of tectoquinone and acteoside from Tectona grandis linn: a new SARS-CoV-2 main protease inhibitor against COVID-19.

Coronavirus disease 2019 (COVID-19), a highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has drastically changed the lifestyle of people around the globe. Due to the lack of specific and effective antiviral drugs, transmission of the disease increases exponentially and makes it more serious and harder to control. Drugs that were assumed to be effective against COVID-19 have failed in various stages of clinical trials and this made the scientific community more disappointed. But, the race of researchers for developing new and effective antiviral to stop the disease progression still continues and our work is one among them. This study is an attempt to analyze the action of Tectoquinone and Acteoside; an important phytocompound, on SARS-CoV2 viral protease via in silico approach. The compounds were selected on the basis of their molecular docking values and they were subjected to molecular dynamics simulations about 50 ns to determine the stability and the thermodynamic feasibility between the target and the ligands. Binding energies like hydrogen bonding, hydrophobic and electrostatic interactions of the complexes were determined after MD simulations. The Pharmacokinetics and drug likeness evaluation of the compounds provide a strong evidence for the use of these compounds in developing drugs for clinical trials. Thus, the current study reveals the potential phytoconstituents present in Tectona grandis Linn to inhibit COVID-19 viral protease and thereby act as a lead therapeutic agent.Communicated by Ramaswamy H. Sarma.

Potential of artificial intelligence to accelerate diagnosis and drug discovery for COVID-19.

The coronavirus disease (COVID-19) pandemic has caused havoc worldwide. The tests currently used to diagnose COVID-19 are based on real time reverse transcription polymerase chain reaction (RT-PCR), computed tomography medical imaging techniques and immunoassays. It takes 2 days to obtain results from the RT-PCR test and also shortage of test kits creating a requirement for alternate and rapid methods to accurately diagnose COVID-19. Application of artificial intelligence technologies such as the Internet of Things, machine learning tools and big data analysis to COVID-19 diagnosis could yield rapid and accurate results. The neural networks and machine learning tools can also be used to develop potential drug molecules. Pharmaceutical companies face challenges linked to the costs of drug molecules, research and development efforts, reduced efficiency of drugs, safety concerns and the conduct of clinical trials. In this review, relevant features of artificial intelligence and their potential applications in COVID-19 diagnosis and drug development are highlighted.

In silico sgRNA tool design for CRISPR control of quorum sensing in Acinetobacter species.

CRISPR genome editing utilizes Cas9 nuclease and single guide RNA (sgRNA), which directs the nuclease to a specific site in the genome and makes a double-stranded break (DSB). Design of sgRNA for CRISPR-Cas targeting, and to promote CRISPR adaptation, uses a regulatory mechanism that ensures maximum CRISPR-Cas9 system functions when a bacterial population is at highest risk of phage infection. Acinetobacter baumannii is the most regularly identified gram-negative bacterium infecting patients. Recent reports have demonstrated that the extent of diseases caused by A. baumannii is expanding and, in a few cases, now surpasses the quantity of infections caused by P. aeruginosa. Most Acinetobacter strains possess biofilm-forming ability, which plays a major role in virulence and drug resistance. Biofilm bacteria use quorum sensing, a cell-to-cell communication process, to activate gene expression. Many genes are involved in biofilm formation and the mechanism to disrupt the biofilm network is still not clearly understood. In this study, we performed in silico gene editing to exploit the AbaI gene, responsible for biofilm formation. The study explored different tools available for genome editing to create gene knockouts, selecting the A. baumannii AbaI gene as a target.